List of tables A1. A2. A3. A4. B1. B2. B3. B4. B5. B6. B7. B8. B9. B10. B11. B12. B13. B14. B15. B16. B17. B18. B19. B20. B21. B22. B23. C1. C2.

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1 Appendices

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3 List of tables A1. Estimated average level of mechanization by region 101 A2. Summary of the allocation techniques used in the calculation of plant-based feed emissions 103 A3. Example of allocation between edible products from dairy production 107 A4. Example of allocation between non-edible (wool) and edible products from sheep dairy production 108 B1. Spatial resolution of the main input variables 112 B2. Herd parameters for dairy cattle, regional averages 113 B3. Herd parameters for beef cattle, regional averages 114 B4. Herd parameters for goats, regional averages 114 B5. Herd parameters for sheep, regional averages 115 B6. Herd parameters for buffalo, regional averages 115 B7. Dairy cattle feed ration, regional averages 117 B8. Beef cattle feed ration, regional averages 117 B9. Dairy buffalo feed ration, regional averages 118 B10. Buffalo meat feed ration, regional averages 118 B11. Small ruminant milk feed ration, regional averages 119 B12. Small ruminant meat feed ration, regional averages 119 B13. Calculated feed digestibility, regional averages 120 B14. Emissions factors for fuel consumption 120 B15. Dairy cattle manure management systems, regional averages 120 B16. Beef cattle manure management systems, regional averages 121 B17. Buffalo milk production manure management systems, regional averages 121 B18. Buffalo meat production manure management systems, regional averages 121 B19. Small ruminant manure management systems, regional averages 122 B20. Dressing percentages for large ruminants 122 B21. Dressing percentages for small ruminants 123 B22. Percentage of dairy and beef herds, ratio of beef production from cattle herds and emission allocation factor for milk and meat from the dairy herd 123 B23. Emission allocation factors for sheep 124 C1. Global area expansion for selected crops with highest area expansion ( ) 134 C2. Average annual land-use change rates in Argentina and Brazil ( )

4 C3. Net changes in area for main land use categories ( ) 136 C4. Pasture expansion against forestland in Latin America ( ) 137 C5. Country specific estimates of above-and below-ground biomass 138 C6. Default soil organic C stocks for mineral soils 140 C7. Soil organic carbon pool at 0-30 cm depth 140 C8. Alternative approaches for soybean LUC emissions calculations 141 C9. Summary of soybean LUC emission intensity for the four approaches 143 C10. Proportion of expanded soybean area derived from each land use category 143 C11. Estimated changes in pasture area and annual carbon losses for the reduced time-frame approach 144 C12. Soybean LUC emissions per unit of output and hectare 145 C13. Comparison of studies on LUC associated with pasture expansion in Brazil 146 C14. Total GHG emissions from the ruminant sector in the European Union and changes in C stocks in permanent pasture 147 D1. Average regional specific CO 2 emissions per MJ from electricity and heat generation 154 D2. Emission intensity for road transport 157 D3. Average emissions intensities associated with road transport from plant to retail 157 D4. International trade in beef, D5. Emission intensity for ocean transport 158 D6. Regional emission factors for processing of beef and lamb 159 E1. Typology of animal housing considered in this assessment 162 E2. An example of a life cycle inventory for a high investment structure for small ruminants 162 E3. Allocation of embedded energy in housing an example for small ruminants in arid zones in OECD countries 162 E4. Milking, cooling and storage equipment considered in this assessment 164 E5. Average emission factors for embedded energy for dairy cattle 165 E6. Average emission factors for embedded energy for dairy sheep and goats 165 E7. Total on-farm direct energy use and associated emissions for high level dairy farms 165 E8. Emissions from direct energy for different levels of mechanization 166 E9. Emission factors for direct on-farm energy use for dairy cow milk production in OECD and non-oecd countries 166 E10. Regional emission factors for direct on-farm energy use 167 F1. Beef cattle products and by-products, by type of use 171 F2. Total revenue from one adult cattle sold by the slaughterhouse and share of by-products 173 F3. Emissions intensity of beef with and without allocation to slaughter by-products in Western Europe

5 List of figures A1. Schematic representation of GLEAM 97 A2. Structure of herd dynamics for cattle 98 C1. Net land conversion between 1990 and 2006, by region 133 C2. Maize and soybean area expansion between 1990 and 2006, by region 134 C3. Main soil classes in Latin American forested areas based on the World Reference Base for Soil Resources classification 139 C4. Annual forest loss in Brazil

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7 APPENDIX A The Global livestock environmental assessment model (GLEAM) 1. Introduction The Global Livestock Environmental Assessment Model (GLEAM) is a processbased static model that simulates the functioning of livestock production systems. The current version of the model (V1.0) focuses primarily on the quantification of GHG emissions, but future versions will include other processes and flows for the assessment of other environmental impacts, such as those related to water, nutrient and land use. The model differentiates the 11 main livestock commodities, which are: meat and milk from cattle, sheep, goats and buffalo; meat from pigs; and meat and eggs from chickens. It calculates the GHG emissions and production for a given production system within a defined spatial area, thereby enabling the calculation of the emission intensity for combinations of commodities, farming systems and locations. The main purpose of this appendix is to explain the way in which GLEAM calculates the emission intensity of livestock products. The input data used in GLEAM (and associated issues of data quality and management) are addressed in Appendix B. The focus of this appendix is on: providing an overview of the main stages of the calculations; outlining the formulae used; and explaining some of the key assumptions and methodological choices made. 2. Model overview The model is GIS-based and consists of: input data layers; routines written in Python ( that calculate intermediate and output parameters; and procedures for running the model, checking calculations and extracting output. The basic spatial unit used in the GIS is a cell of 3 arc minutes. The emissions and production are calculated for each cell using input data of varying levels of spatial resolution (see Appendix B). The overall structure of GLEAM is shown in Figure A1, and the purpose of each module summarized below. The herd module starts with the total number of animals of a given species and system within a cell (see Appendix B for a brief description of the way in which the total animal numbers are determined). The module also determines the herd structure (i.e. the number of animals in each cohort group, and the rate at which animals move between cohort groups) and the characteristics of the average animal in each cohort (e.g. weight and growth rate). The manure module calculates the rate at which excreted N is applied to pasture and crops. 95

8 Greenhouse gas emissions from ruminant supply chains The feed module calculates key feed parameters, i.e. the nutritional content and emissions per kg of the feed ration. The system module calculates each animal s energy requirement, and the total amount of animal product (milk, meat and fibre) produced in the cell each year. It also calculates the total annual emissions arising from manure management, enteric fermentation and feed production. The allocation module combines the emissions from the system module with the emissions calculated outside GLEAM, i.e. emissions arising from (a) direct on-farm energy use; (b) the construction of farm buildings and manufacture of equipment; and (c) post-farm transport and processing. The total emissions are then allocated to output in the form of products and services (milk, meat and eggs, fibre and draught power) and the emission intensity per unit of commodity calculated. Each of the stages in the model is described in more detail below. 3 Herd module The functions of the herd module are to: Determinate the herd structure, i.e. the proportion of animals in each cohort, and the rate at which animals move between cohorts; and Calculate the characteristics of the animals in each cohort, i.e. the average weight and growth rate of adult females and adult males. Emissions from livestock vary depending on animal type, weight, phase of production (e.g. whether lactating or pregnant) and feeding situation. Accounting for these variations in a population is important if emissions are to be accurately characterized. The use of the IPCC (2006) Tier 2 methodology requires the animal population to be categorized into distinct cohorts. Data on animal herd structure are generally not available at the national level. Consequently, a specific herd module was developed to decompose the herd into cohorts. The herd module characterizes the livestock population by cohort, defining the herd structure, dynamics and production. Herd structure. The national herd is disaggregated into six cohorts of distinct animal classes: adult female and adult male, replacement female and replacement male, and male and female surplus or fattening animals which are not required for maintaining the herd. Figure A2 provides an example of a herd structure (in this case for cattle). In this assessment it is assumed that all surplus calves are fattened for meat. 12 The key production parameters required for herd modeling include data on mortality, fertility, growth and replacement rates, also known as rate parameters. In addition, other parameters are used to define the herd structure. They include: the age or weight at which animals transfer between categories e.g. the age at first parturition for replacement females or the weight at slaughter for fattening animals; duration of key periods i.e. gestation, lactation, time between servicing; and the ratio of breeding females to males. 12 In some intensive dairy systems, surplus calves may be slaughtered within a few days after birth. 96

9 Appendix A - The Global Livestock Environmental Assessment Model (GLEAM) Figure A1. Schematic representation of GLEAM Total number of animals in a cell, of a given system and species (e.g. backyard pigs) Herd parameters (e.g. mortality, fer lity, and replacement rates) HERD MODULE Calcula on of herd structure MANURE MODULE Calcula on of rate of manure applica on to grass & crops * kg of manure N applied per ha * * Number of animals in each cohort Average weights and growth rates Values for protein content of meat, milk and eggs Ac vity level adjusts the maintenance energy to account for the addi onal energy required for animals ranging or scavenging for food Data on selected environmental parameters, e.g. average annual temperature, leaching rates Assump ons about how manure is managed CH 4 and N 2 O emission factors for manure management system Bo manure maximum methane producing capacity SYSTEM MODULE Calcula on of: - each animal s energy requirements - each animal s feed intake - emissions from feed - each animal s rates of vola le solids and N excre on - emission from manure - enteric methane - total produc on of meat/milk/eggs * * Total produc on (of meat, milk and eggs) for each animal category Total emissions for each animal category DIRECT AND INDIRECT ENERGY EMISSIONS ALLOCATION MODULE Calcula on of the emissions per kg of product * Input data taken from literature review, exis ng databases and expert knowledge Intermediate data (model generated) Source: Authors. Assump ons about animal ra ons (i.e. propor ons of feed material in the ra on) Crop yields Synthe c N applica on rates Emission factors for N 2 O Energy use in fieldwork, transport and processing Emission factors for different fuel types Nutri onal values of feed materials Land-use change emissions factors Land-use change soybean produc on & pasture expansion Rice CH 4 emission factor FEED MODULE - Determina on of percentage of each feed material in ra on - Calcula on of CO 2, N 2 O and CH 4 emissions per ha for each feed material - Alloca on of emissions to crop, crop residues and by-products - Calcula on of emissions and nutri onal values per kg of ra on * ** * ME, DE and GE per kg DM kg N/kg DM kg CO 2 -eq/kg DM ha/kg DM Conversion factors: dressing percentage bone-free meat percentage protein content POSTFARM EMISSIONS 97

10 Greenhouse gas emissions from ruminant supply chains Figure A2. Structure of herd dynamics for cattle Calves Calves Adult female Sale Death In-calf heifers Replacement female Sale Death Adult male Sale Death Young bulls and oxen Replacement male Sale Death Male and female surplus calves Sale Death Source: Authors. 4. Manure module The function of the manure module is to calculate the rate at which excreted N is applied to feed crops. The manure module calculates the amount of manure N collected and applied to grass and cropland in each cell by: calculating the amount of N excreted in each cell by multiplying the number of each animal type in the cell by the average N excretion rates; calculating the proportion of the excreted N that is lost during manure management and subtracting it from the total N, to arrive at the net N available for application to land; and dividing the net N by the area of (arable and grass) land in the cell to determine the rate of N application per ha. 5. Feed module The functions of the feed module are to: Calculate the composition of the ration for each species, system and location; Calculate the nutritional values of the ration per kg of feed DM; and Calculate of GHG emissions and land use per kg of DM of ration. The feed module determines the diet of the animal, i.e. the percentage of each feed material in the ration, and calculates the emissions (N 2 O, CO 2 and CH 4 ) arising from the production, processing and transport of the feed. It allocates the emissions to crop co-products such as crop residues or meals) and calculates the emission intensity per kg of feed. It also calculates the nutritional value of the ration, in terms of its energy and N content. 5.1 Determination of the ration Animal rations are generally a combination of different feed ingredients. For ruminants, three broad categories of feed are considered: roughages, by-products and concentrates. Typically, major feed ingredients include: 98

11 Appendix A - The Global Livestock Environmental Assessment Model (GLEAM) Grass: ranges from natural pasture and roadsides to improved and cultivated grasslands and leys. Feed crops: crops specially grown to feed livestock, e.g. maize silage or grains. Tree leaves: browsed in forests or collected and carried to livestock. Crop residues: plant material left over from food or other crops, such as straw or stover, left over after harvesting. Agro-industrial by-products and wastes: by-products from the processing of non-feed crops such as oilseeds, cereals, sugarcane, and fruit. Examples include cottonseed cakes, rapeseed cakes and brans. Concentrates: high quality mixtures of by-products and feed that are processed at specialized feed mills into compound feed. In all livestock production systems, the composition of the feed ration depends on the availability of pasture and fodder, the crops grown and their respective yields. The fraction of concentrates in the ration varies widely, according to the need to complement locally available feed, the purchasing power of farmers, and access to markets. While actual diets will vary depending on what crops are grown locally and the price of feed crops, the balance of forage, crops and by-products must be reasonable in order to match animal performance. The proportion of each feed component is determined differently for industrialized and developing country regions: for the industrialized regions, the composition (i.e. feed materials) and relative portions of the feed ration materials are taken from country national inventory reports, literature and targeted surveys. for developing countries, due to scanty information, a feed allocation scheme was devised based on literature and expert knowledge. This allocation scheme assumes that in developing regions there is a close relationship between land use and the feed ration. Feed allocation scheme for developing countries. The feed allocation scheme is based on the availability of feed resources (crops and forage) and animal requirements. The determination of the feed ration is outlined stepwise below: 1. Define the proportion of by-products and concentrates in the ration (based on surveys, literature and expert knowledge) and the difference is considered roughages. 2. Calculate the total roughage availability in each pixel based on the dry matter yields per hectare of pasture, fodder and crop residues and the land area of the respective feeds. Data for this calculation was obtained from a number of sources: FAOSTAT for specific crops (e.g. fodder beet, soybean, rapeseed, cottonseed, sugar beet and palm fruit); You et al. (2010) from the Spatial Production Allocation Model (SPAM) for 20 crops; and Haberl et al. (2007) to estimate the above-ground net primary productivity for pasture. 3. Feed requirements for all ruminant species were then assessed. This was done by expressing the different ruminant species and categories of animals in cattle equivalent, to take into account the fact that these animals are competing for the same feed resource. 4. To assess the feed availability, a ratio between the total roughage availability (calculated in 2 above) and ruminant species biomass (in cow equivalent calculated in 3 above) was obtained. 99

12 Greenhouse gas emissions from ruminant supply chains 5. Total ruminant annual feed requirements are then calculated for the total cow equivalent based on the assumption that an animal consumes about 2 to 3 percent of its bodyweight on a daily basis and hence, on an annual basis, DMI will range between 7.3 and 14 kg DM. 6. The total amount of roughage feed available is then compared with the animal feed requirements within each cell. Comparing the total feed availability with the animal requirements provides an indication of feed adequacy in terms of sufficiency, deficiency or surplus for any given location. An area can be classified based on the dry matter availability and generally a dry matter availability of less than 2 percent of the bodyweight can be considered as a deficit, dry matter availability between 2 and 3 percent can be considered as adequate, and above 3 percent can be considered as surplus. In situations where ample feed is not available to meet the requirements of the animals (i.e. less than 2 percent), the feed ration is supplemented with leaves and hay. 7. The proportion of each roughage material within the feed ration is then obtained by dividing the quantity available of each roughage material by the total available roughage. 8. The proportions of the roughage materials (calculated in 7 above) plus the by-products and concentrate proportions (defined in 1 above) form the total feed ration which sums to 100. Tables B7 to B12 in Appendix B present the average feed rations and the proportions of the different feed materials within the feed ration for the world s main regions and species. 5.2 Determination of the ration s nutritional values Nutritional values such as the digestibility and N-content of each individual feed material are used to calculate the nutritional value of animal feed rations. These nutritional values are multiplied by the percentage of each feed material in the ration to arrive at the average energy and N content per kg of DM for the ration as a whole. Table B13 in Appendix B compares regional variation in digestibility of feed rations for ruminant species. 5.3 Determination of the ration s GHG emissions and land use per kg of DM from feed The categories of GHG emission included in the assessment of each feed material s emissions are: direct and indirect N 2 O from grass and crop cultivation; CO 2 arising from loss of above and below ground carbon brought by landuse change; CO 2 from the on-farm energy use associated with field operations (tillage, manure application, etc.) and crop drying and storage; CO 2 arising from the manufacture of fertilizer; CO 2 arising from crop transport; and CO 2 arising from off-farm crop processing. A brief outline of how the emissions were calculated is provided below. Determination of feed emissions: N 2 O from pasture and crop cultivation. Nitrous oxide emissions from cropping include direct N 2 O, and indirect N 2 O from leach- 100

13 Appendix A - The Global Livestock Environmental Assessment Model (GLEAM) ing and volatilization of ammonia. It was calculated using the IPCC (2006) Tier 1 methodology. Synthetic N application rates were defined for each crop at a national level, based on existing data sets (primarily FAO s fertilizer use statistics, and adjusted down where yields were below certain thresholds. Manure N application rates were calculated in the manure module. Crop residue N was calculated using the crop yields and the IPCC (2006, Volume 4, Chapter 11, p ) crop residue formulae. Determination of pasture and crop emissions: CO 2 from land-use change. The approach for estimating emissions from land-use change is presented in Appendix C. Determination of feed emissions: CO 2 from fertilizer manufacture. The manufacture of synthetic fertilizer is an energy-intensive process, which can produce significant amounts of GHG emissions, primarily via the use of fossil fuels, or through electricity generated using fossil fuels. The emissions per kg of fertilizer N will vary depending on the factors such as the type of fertilizer, the efficiency of the production process, the way in which the electricity is generated, and the distance the fertilizer is transported. Due to the lack of reliable data on these parameters, and on fertilizer trade flow, the average European fertilizer emissions factor of 6.8 kg CO 2 - eq per kg of ammonium nitrate N in all regions was used (Jenssen and Kongshaug, 2003), which includes N 2 O emissions arising during manufacture. Determination of feed emissions: CO 2 from field operations. Energy is used on-farm for a variety of field operations required for crop cultivation, such as tillage, preparation of the seed bed, sowing and application of synthetic and organic fertilizers, crop protection and harvesting. The type and amount of energy required per ha, or kg, of each feed material parent crop was estimated. In some countries, field operations are undertaken using non-mechanized power sources, i.e. human or animal labour. The energy consumption rates were adjusted to reflect the proportion of the field operations undertaken using non-mechanized power sources. Table A1 gives an indication of the average level of mechanization per region. From the level of mechanization, we also inferred reliance on animal draught power in the country, and therefore the bull to cow ratio in the herd. The emissions arising from fieldwork per ha of each crop were calculated by multiplying the amount of each energy type consumed per ha, by the emissions factor for that energy source. Table A1. Estimated average level of mechanization by region Continent Estimated rate of mechanisation (percentage) Africa 16 Asia 78 Central and South America 96 Europe 100 North America 100 Oceania 100 Source: FAOSTAT (2009). 101

14 Greenhouse gas emissions from ruminant supply chains Determination of feed emissions: CO 2 from transport and processing. Pasture and crop residues, by definition, are transported minimal distances and are allocated zero emissions for transport. Non-local feeds are assumed to be transported between 100 km and 700 km by road to their place of processing. In countries where more of the feed is consumed than is produced (i.e. net importers), feed that are known to be transported globally (e.g. soybean meal) also receive emissions that reflect typical sea transport distances. Emissions from processing arise from the energy consumed in activities such as milling, crushing and heating, which are used to process whole crop materials into specific products. Therefore, this category of emissions applies primarily to feeds in the by-product category. Determination of feed emissions: CO 2 from blending and transport of compound feed. Energy is used in feed mills for blending non-local feed materials to produce compound feed and to transport it to its point of sale. It was assumed that 186 MJ of electricity and 188 MJ of gas were required to blend kg of DM, and that the average transport distance was 200 km. 5.4 Allocation of emissions between crop and its by-products In order to calculate the emission intensity of the feed materials, emissions need to be allocated between the crop and its by-products, i.e. the crop residue or byproducts of crop processing used as feed. The general expression used is: GHGkgDM = GHGha/(DMYGcrop FUEcrop+DMYGby FUEby) EFA/MFA where: GHGkgDM = emissions (of CO 2, N 2 O, or CH 4 ) per kg of dry matter GHGha = emissions per ha DMYGcrop = gross crop yield (kgdm/ha) DMYGby = gross crop residue or by-product yield (kgdm/ha) FUEcrop = feed use efficiency, i.e. fraction of crop gross yield harvested FUEby = feed use efficiency, i.e. fraction of crop residue or by-product gross yield harvested EFA = economic fraction, crop or co-product value as a fraction of the total value (of the crop and co-product) MFA = mass fraction, crop or co-product mass as a fraction of the total mass (of the crop and co-product) Dry matter yields and estimated harvest fractions were used to determine the mass fractions. Where crop residues were not used for feed or bedding, they were assumed to have a value of zero, i.e. 100 percent of the emissions were allocated to the crop. Allocation techniques of feed emissions is summarized in Table A2. Emissions from post-processing blending and transport are allocated entirely to feed. It should be highlighted that emissions that are not allocated to feed do not cease to exist. Rather, they are allocated to other commodities. Failure to follow this approach may lead to incorrect policy conclusions. 102

15 Appendix A - The Global Livestock Environmental Assessment Model (GLEAM) Table A2. Summary of the allocation techniques used in the calculation of plant-based feed emissions Products Source of emissions Allocation technique All feed crops and their by-products N 2 O from manure application N 2 O from synthetic fertilizer CO 2 from fertilizer manufacture CO 2 from fieldwork Allocation between the crop and co-product is based on the mass harvested, and the relative economic values (using digestibility as a proxy) By-products only Feed produced off-farm Source: Authors. CO 2 from processing CO 2 from LUC (for soybean) CO 2 from transportation and blending Allocated to the processing by-products based on mass and economic value 100 percent to feed material 6. System module The functions of the system module are to: Calculate the average energy requirement (MJ) and feed intake (kg DM) of each animal cohort; Calculate the total feed emissions and land use arising from the production, processing and transport of the feed; Calculate the CH 4 and emissions arising during the management of manure; Calculate enteric CH 4 emissions. 6.1 Calculation of animal energy requirement The system module calculates the energy requirements of each animal, which is then used to determine the feed intake (in kg of DM). The model uses the IPCC Tier 2 algorithms (IPCC, 2006 Volume 4, Chapter 10, Equations 10.3 to 10.13) to calculate energy requirements for each animal sub-category. The gross energy requirement is the sum of the requirements for maintenance, lactation and pregnancy, animal activity, weight gain and production. 13 The method estimates a maintenance requirement (as a function of live-weight and energy expended in feeding); a production energy requirement influenced by the level of productivity (e.g. milk yield, live-weight gain, wool production); physiological state (pregnancy and lactation); and the stage of maturity of the animal. Based on production and management practices, the net energy and feed requirements of all animals are first calculated, taking into account the following parameters: Weight. Larger animals need more energy for maintenance than smaller ones. Production. The output from animals can be milk and meat, but also nonedible products and services. Data on production of edible and non-edible products is taken from literature and statistical databases. In general terms, a higher production or more labour per day requires more energy and thus more feed per day. 13 Total production is computed on the basis of herd parameters (reproduction, mortality, etc.) and productivity parameters (such as milk yield and weight gain) used in the analysis. Consequently, total production may not be consistent with total production in the FAOSTAT database. 103

16 Greenhouse gas emissions from ruminant supply chains Production/feeding environment (Grazing or stall feeding). Animals in ranging systems that have to search for their feed (often over long distances) have higher energy requirements than those in grazing systems or stall-fed systems. 6.2 Calculating feed intake, total feed emissions and land use The feed intake of each animal category (in kg DM/day) is calculated by dividing the animal s energy requirement by the average energy content of the ration from the feed module: Feed intake (kgdm/animal/day) = total energy requirements (MJ/animal/day)/feed energy content (MJ/kgDM) where: feed energy content = (MJ/kgDM) The feed intake of each cohort is multiplied by the number of animals in each group to obtain the total daily feed intake for the entire herd. The feed emissions and land use associated with the feed production are then calculated by multiplying the total feed intake for the herd by the emissions or land use per kg of DM taken from the feed module. 6.3 Calculation of CH 4 emissions arising enteric fermentation Emissions from enteric fermentation (kg CH 4 /head) are a function of feed digestibility (DE), i.e. the percentage of gross energy intake that is metabolized. An enteric methane conversion factor, Y m (percentage of gross energy converted to methane) is used to calculate the methane emissions from enteric fermentation. A Tier 2 approach is applied for the calculation of enteric CH 4 emissions due to the sensitivity of emissions to diet composition and the relative importance of enteric CH 4 to the overall GHG emissions profile in ruminant production. The IPCC (2006) defines the CH 4 conversion factor (Y m ) as 6.5±1 percent, indicating that Y m is at the high end of the range when digestibility of feed is low and vice versa. The Y m value of 6.5 is realized at a digestibility of 65 percent. To better reflect the wide-ranging diet quality and feeding characteristics globally, this assessment developed specific Y m values based on the following formula: Y m Cattle = DE Y m mature sheep = DE Y m lamb<1 year = DE Y m is subsequently used in the following formula to estimate the CH 4 emission factor EFCH 4 = (365 GE (Y m / 100) / 55.65) where: EFCH 4 is the CH 4 emission factor (kg CH 4 head -1 yr -1 ); Y m corresponds to CH 4 conversion factor; GE is the gross energy intake (MJ head -1 day -1 ) and the factor (MJ kg CH 4 ) represents the energy content of CH

17 Appendix A - The Global Livestock Environmental Assessment Model (GLEAM) 6.4 Calculation of CH 4 emissions arising during manure management Calculating the CH 4 per head from manure using a Tier 2 approach requires (a) estimation of the rate of excretion of volatile solids per animal, and (b) estimation of the proportion of the volatile solids that are converted to CH 4. The volatile solids excretion rates are calculated using Equation from IPCC (2006). Once the volatile solids excretion rate is known, the proportion of the volatile solids converted to CH 4 during manure management per animal per year can be calculated using Equation from IPCC (2006). The CH 4 conversion factor depends on how the manure is managed. In this study, the manure management categories and emission factors in IPCC (2006, Volume 4, Chapter 10, Table 10A-7) were used. The proportion of manure managed in each system is based on official statistics (such as the Annex I countries National Inventory Reports to the UNFCCC), other literature sources and expert judgement. 6.5 Calculation of N 2 O emissions arising during manure management Calculating the N 2 O per head from manure using a Tier 2 approach requires (a) estimation of the rate of N excretion per animal, and (b) estimation of the proportion of the excreted N that is converted to N 2 O. The N excretion rates are calculated using Equation from IPCC (2006) as the difference between intake and retention. N-intake depends on the feed dry matter intake and the N content per kg of feed. The feed dry matter intake depends, in turn, on the animal s energy requirement (which is calculated in the system module, and varies depending on weight, growth rate, milk yield, pregnancy, weight gain and lactation rate and level of activity) and the feed energy content (calculated in the feed module). N retention is the amount of N retained in, either as growth, pregnancy live weight gain or milk. The rate of conversion of excreted N to N 2 O depends on the extent to which the conditions required for nitrification, denitrification, leaching and volatilization are present during manure management. The IPCC (2006) default emission factors for direct N 2 O (IPCC, 2006 Volume 4, Chapter 10, Table 10.21) and indirect via volatilization (IPCC, 2006 Volume 4, Chapter 10, Table 10.22) are used in this study, along with variable leaching rates, depending on the AEZ. 7. Allocation module The functions of allocation module are to: Sum up the total emissions for each animal cohort; Calculate the amount of each commodity (meat, milk, eggs, wool) produced; Allocate emissions to each commodity (meat and meat), non-edible outputs (fibre and manure used for fuel), draught and services; and Calculate total emissions and emission intensity of each commodity. 7.1 Calculation of the total emissions for each animal cohort The system module calculates the total emissions arising from feed production, manure management and enteric fermentation. Post farmgate emissions (Appendix D) and direct and indirect on-farm energy use (Appendix E) are calculated separately and incorporated in the allocation module. 105

18 Greenhouse gas emissions from ruminant supply chains 7.2 Calculation of the amount of each commodity (meat, milk, fibre) produced Milk. Total milk production was calculated based on average milk production per animal and number of milking animals. Total milk is then converted to fat and protein milk. Using FPCM as the basis for comparison ensures a comparison between milk produced by different breeds and feeding regimes. All milk was converted to FPCM using the following equations: Milk yield from cattle was corrected at 4.0 percent fat and 3.3 percent protein using the equation: FPCM (kg) = milk production, kg [ fat, (percent) protein, (percent)] Milk yield from small ruminants was corrected at 6.5 percent fat and 5.8 percent protein according to Pulina, Macciotta and Nuda (2004) using the equation: FPCM (kg) = milk production, kg [ fat, (percent) protein, (percent)] Buffalo milk production was expressed was corrected at 4 percent fat and 3.1 percent protein using the following equation (Di Palo, 1992): FPCM (kg) = milk production, kg [ {(fat, (percent) 10-40) + (10 protein, (percent)-31)}] Meat. Total meat production is calculated from the number of live animals (per cohort group) that leave the farm for slaughter and the live weight at which they are sold. Dressing percentages for the conversion of live weight to carcass weight are given in Appendix B, Tables B20 and B21. Conversion of carcass to bone-free meat is obtained by multiplying by 0.75 and 0.70 for large and small ruminants, respectively. The conversion of bone-free meat (BFM) to protein is based on the assumption that BFM is 18 percent protein by weight. Natural fibre. Total fibre (wool, mohair and cashmere) is estimated by multiplying kg of fibre produced per animal by the number of fibre producing animals in the herd. 7.3 Allocation to co-products and calculation of emission intensity For ruminant species, emissions are allocated between the edible commodities, i.e. meat and milk. In reality, there are usually significant amounts of other commodities produced during processing, such as skin, feathers and offal. However, the values of these can vary markedly between countries, depending on the market conditions, which, in turn, depend on factors such as food safety regulations and consumer preferences. Allocating no emissions to these can lead to an over-allocation to meat. The potential effect of this assumption is explored in Appendix F. Allocation techniques applied in this assessment are discussed below: Meat and milk. Emissions related to goods and services other than meat and milk (e.g. fibre, manure used for fuel, draught power) were first calculated separately and deducted from the overall system emissions, before emissions were attributed to meat and milk. Within the dairy herd, some animals only produce meat (fattened surplus calves), while others contribute to the combined production of meat and dairy products (milked cows, adult reproduction male animals and replacement stock). For the latter group, we chose to allocate GHG emissions on the basis of their protein con- 106

19 Appendix A - The Global Livestock Environmental Assessment Model (GLEAM) Table A3. Example of allocation between edible products from dairy production Part of herd producing milk and meat (milking cows, adult male, replacement stock) Part of herd producing meat only (surplus males and females) Total emissions (kg CO 2 -eq) Total protein (kg) Milk: Meat: Meat: Fraction of milk protein 0.92 NA Fraction of meat protein Emission intensity of milk = ( )/ = 87 kg CO 2 -eq/kg protein Emission intensity of meat = [( ) ]/( ) 122 kg CO 2 -eq/kg protein NA: Not Applicable. Source: Authors calculations. tent. Table A3 provides an illustration of how the technique is applied. This method reflects the fact that a primary function of the livestock sector is to provide humans with edible protein. The advantages of using protein content are that it enables direct comparison with other food products and is also relatively stable in time (as opposed, for example, to the relative prices of meat and milk) and that it can be applied in situations where markets are absent or where they are highly localized and not comparable across regions. However, a disadvantage is that other nutritional properties, such as minerals, vitamins and energy, and essential fatty acids are not captured. Emissions related to surplus calves fattened for meat production were entirely attributed to meat production. However, the emissions related to the production of calves, i.e. the pregnancy of the dairy cows and female replacement stocks, were allocated to milk because they are an essential input for milk production. No emissions were allocated to the other parts of the slaughtered animal (e.g. skin, horns), although these are utilized and represent an economic yield. This may result in a slight overestimation of the emissions per kg of carcass weight. In beef herds, all emissions were allocated to meat after the deduction of emissions related to draught power (in the case of cattle) and fibre (wool, cashmere and mohair) from small ruminants. Manure. Manure is another by-product of livestock production. The emissions related to manure were allocated through the subdivision of the production processes: Emissions related to manure storage were fully allocated to the livestock system. Emission from manure applied on the land used for feed, food and cash crop production were allocated to livestock in situations where the crop as a whole or in part (e.g. silage, grain, oilseeds) was used for animal nutrition. In situations where manure was entirely deposited on grassland and feed crops, no allocation was required because the manure remained within the livestock system. On the other hand, where parts of the crop (e.g. crop residues) were used for feed, emissions were allocated according to the relative weight of harvested products used as feed, corrected for digestibility. Due to 107

20 Greenhouse gas emissions from ruminant supply chains the absence of an economic value for crop residues, digestibility was used as a proxy for economic value. In cases where the crop was not used for animal nutrition, emissions were not allocated to livestock. Emissions from manure used for fuel at the household level leave the livestock system and therefore emissions from burning were not allocated to the livestock system. Emissions from manure discharged into the environment were solely attributed to livestock activities. Fibre (wool, cashmere and mohair). Fibre is a by-product of sheep and goat production; however in some countries these products can be considered as main products of production due to their price leverage and market value. In this study, the allocation of the carbon footprint to fibre was performed based on the market value of all system outputs meat, milk, and fibre products. The fractions of the economic value of the co-product within the total economic value of all products produced by a given species were utilized as an allocation factor to partition GHG emissions between fibre and the edible products. This fraction was determined as: F w = (Wool kg Price wool )/(Meat kg Price meat + Milk kg Price milk + Wool kg Price wool ) where: F w is the ratio of economic value of wool to the total economic value of all products produced. Similar calculations were performed for countries producing cashmere and mohair. Wool, meat and milk represent the mass of the product in kg. Table A4 provides an illustration of how the technique is applied. To implement the total economic value, producers prices averaged over five years were taken from the FAOSTAT price domain, reflecting prices that farmers receive at the farmgate. Subsequent to the deduction of emissions for fibre production from the overall emissions, protein content was then used to allocate emissions between meat and milk. Table A4. Example of allocation between non-edible (wool) and edible products from sheep dairy production Part of herd producing milk, meat and wool Part of herd producing meat and wool only Total emissions (kg CO 2 -eq) ,000 Total protein (kg) Milk: 500 Meat: 50 Meat: 200 Total economic value ($) Milk: Meat: Wool: 700 Fraction of milk protein 0.9 NA Fraction of meat protein Total emission allocated to wool Total emissions allocated to milk and meat = [700/( )] = kg CO 2 -eq = = kg CO 2 -eq = [700/( )] = kg CO 2 -eq = = kg CO 2 -eq Emission intensity of milk = ( )/500 = 138 kg CO 2 -eq/kg protein Emission intensity of meat = [( ) ]/(50+200) = 104 kg CO 2 -eq/kg protein NA: Not Applicable. Source: Authors calculations. 108

21 Appendix A - The Global Livestock Environmental Assessment Model (GLEAM) Animal draught power. Herd structure, and thus the emissions profile, is affected by the use of animals, usually oxen, for labour. The use of animals for draught power has an influence on the herd s sex and age structure which skews towards higher ratios of male and older animals. Oxen must grow to maturity before they can be used for traction, and this usually takes four years, and therefore they compete with other stock for feed and other resources. The animals are then generally used for a decade before they are slaughtered. The adult male to female ratio is substantially higher than normal when animals are used for draught power because males are slaughtered at a later age. To allocate emissions to draught power services, we first calculated total emissions and meat output from draught animals alone. In a subsequent calculation step, emissions related to the meat produced from these animals were estimated as being identical to those of meat produced from non-draught animals, slaughtered at an earlier age. The difference (accruing from the extra lifetime and the energy requirements for the labour of draught animals) was then attributed to draught power services. Capital functions of cattle. In any cattle production system, animals constitute a form of capital, and can be sold or bought according to investment and cash flow requirements. In many pastoral systems, the capital functions of cattle are a particularly important, because they enable the accrual of savings to manage cash needs, insure against risk, and manage crises in the absence of adequate financial institutions. Therefore, low replacement rates are often a feature in these systems, because cattle are often kept even after their productivity drops. While the provision of these capital functions affects the herd structure and emission profiles of these systems, no emissions were allocated to capital services, due to difficulties in obtaining relevant information. Slaughter by-products. In addition to the production of carcasses, slaughtering processes also produce a whole package of by-products, organs, hide, blood, etc. that are utilized for other purposes, often outside the livestock food chain. Thus, the allocation of emissions to by-products produced at the slaughterhouse can have a major impact on the GHG emission intensity for meat products. This study did not explicitly take into account by-products from slaughter due to the lack of reliable information and data. However, we explored the impact of their inclusion on emission intensity of beef in a selected case study (see Appendix F). In terms of edible product, ruminants produce both milk and meat. The emissions were allocated between these two commodities, using the following method: Quantify the total emissions from animals required for milk and meat production (adult female and adult male, replacement stock and surplus animals). Deduct emissions related to draft power (for large ruminants), and manure used for fuel based on the approaches outlines above. For the dairy sector, which produces both milk and meat, emissions are allocated on a protein basis (see Tables A3 and A4). For small ruminants, allocation is first performed between the edible and non-edible products based on economic value and subsequently protein content is used to allocate between milk and meat. 109

22 Greenhouse gas emissions from ruminant supply chains References Di Palo, R Produzione lattea nella bufala con diete tradizionali e con impiego di acidi grassi. PhD thesis, Università di Napoli. FAO Gridded livestock of the world 2007 by Wint, W. and Robinson, T. FAO. Rome. FERTISTAT Fertilizer use statistics, FAO. Haberl, H., Erb, K. H., Krausmann, F., Gaube, V., Bondeau, A., Plutzar, C., Gingrich, S., Lucht W. & Fischer-Kowalski M Quantifying and mapping the global human appropriation of net primary production in Earth s terrestrial ecosystem. Proceedings of the National Academy of Sciences of the USA 104: IPCC IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4: Agriculture, Forestry and Other Land Use. Intergovernmental Panel on Climate Change. Prepared by the National Greenhouse Gas Inventories Programme, Eggleston, H.S., Buendia, L., Miwa, K., Ngara, T. & Tanabe K. eds. Published: IGES, Japan. Jenssen, T.K. & Kongshaug, G Energy consumption and greenhouse gas emissions in fertiliser production. IFS Proceedings No.509. International Fertiliser Society. York. Pulina, G., Macciotta, N. & Nuda, A Milk composition and feeding in the Italian dairy sheep. Ital. J. Anim. Sci., 4(SUPPL. 1): You, L., Crespo, S., Guo, Z., Koo, J., Ojo, W., Sebastian, K., Tenorio, T.N., Wood, S. & Wood-Sichra, U Spatial Production Allocation Model (SPAM) 2000, Version 3. Release 2. Available at 110

23 APPENDIX B Data and data sources This appendix presents the main data utilized in this assessment. The data can be classified into basic input data and intermediate data. Basic input data can be defined as primary data such as animal numbers, herd parameters, mineral fertilizer application rates, temperature, crop yields, etc. and are data taken from other sources such as literature, databases, and surveys. Intermediate data are an output of the modelling procedure required in further calculation in GLEAM and may include data on growth rates, animal cohort groups, feed rations, animal energy requirements, feed intake, etc. 1. data resolution and disaggregation Data availability, quality and resolution vary according to the parameter and the country in question. In OECD countries, where farming tends to be more regulated, there are often comprehensive national or regional data sets, and in some cases sub-national data (e.g. for manure management in U.S. dairy). Conversely, in many non-oecd countries, data are unavailable, necessitating the use of regional default values (e.g. herd parameters). Examples of the spatial resolution of some key parameters are given in Table B1. 2. Herd Livestock distributions. Maps of the spatial distribution of each animal species and production systems are one of the key inputs into the GLEAM model. Total ruminant numbers at a national level are reported in FAOSTAT. The spatial distributions used in this study were based on maps developed in the context of FAO s Gridded Livestock of the World (FAO, 2007). Herd parameters. The national herd is disaggregated into cohorts according to six animal classes: adult female and male, replacement female and male, and male and female surplus or fattening animals that are not required for maintaining the herd and are kept for meat production only. The key biological parameters required for herd modelling incorporate data on mortality, fertility and growth rate, also known as rate parameters. Fertility parameters: data on fertility are usually incorporated in the form of parturition rates (e.g. calving, kidding, lambing rates), and are normally defined as the number of births occurring in a specified female population in a year. For cattle, the number of births per year is assumed to be one. However, in the case of small ruminants, litter size is taken into account. The model utilizes age-specific fertility rates for adult and young replacement females. The proportion of breeding females that fail to conceive is also included. Mortality rates: data on mortality are incorporated in the form of death rates. In the modelling process, age specific death rates are used; mortality rate in calves and mortality rate in other animal categories. The death rate of 111